Evidence map›Paper›PMID 24388494›Full record

Trial reportMolecular oncology2014

Establishment of a human 3D lung cancer model based on a biological tissue matrix combined with a Boolean in silico model.

Anna T Stratmann, David Fecher, Gaby Wangorsch, Claudia Göttlich, Thorsten Walles, Heike Walles, Thomas Dandekar, Gudrun Dandekar, Sarah L Nietzer

Open access · hybridAbstract readClinical Trial
In one paragraph

Trial report in Molecular oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 85 citations in OpenAlex.

  1. Pooled it
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  7. Article
  8. A novelFrontiers in bioengineering and biotechnology · 2023
    Article
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  11. Article
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  18. Toward a Long-Term Artificial Lung.ASAIO journal (American Society for Artificial Internal Organs : 1992) · 2020
    Review
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Anna T StratmannDepartment of Tissue Engineering and Regenerative Medicine, University Hospital of Wuerzburg, Roentgenring 11, 97070 Wuerzburg, Germany.
David FecherDepartment of Tissue Engineering and Regenerative Medicine, University Hospital of Wuerzburg, Roentgenring 11, 97070 Wuerzburg, Germany.
Gaby WangorschDepartment of Bioinformatics, University Wuerzburg, Am Hubland/Biozentrum, 97074 Wuerzburg, Germany.
Claudia GöttlichDepartment of Tissue Engineering and Regenerative Medicine, University Hospital of Wuerzburg, Roentgenring 11, 97070 Wuerzburg, Germany.
Thorsten WallesDepartment of Cardiothoracic Surgery, University Hospital of Wuerzburg, Oberduerrbacher Str. 6, 97080 Wuerzburg, Germany.
Heike WallesDepartment of Tissue Engineering and Regenerative Medicine, University Hospital of Wuerzburg, Roentgenring 11, 97070 Wuerzburg, Germany.
Thomas DandekarDepartment of Bioinformatics, University Wuerzburg, Am Hubland/Biozentrum, 97074 Wuerzburg, Germany. Electronic address: dandekar@biozentrum.uni-wuerzburg.de.
Gudrun DandekarDepartment of Tissue Engineering and Regenerative Medicine, University Hospital of Wuerzburg, Roentgenring 11, 97070 Wuerzburg, Germany. Electronic address: gudrun.dandekar@uni-wuerzburg.de.
Sarah L NietzerDepartment of Tissue Engineering and Regenerative Medicine, University Hospital of Wuerzburg, Roentgenring 11, 97070 Wuerzburg, Germany.
Universitätsklinikum Würzburg · DEUniversity of Würzburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For the development of new treatment strategies against cancer, understanding signaling networks and their changes upon drug response is a promising approach to identify new drug targets and biomarker profiles. Pre-requisites are tumor models with multiple read-out options that accurately reflect the clinical situation. Tissue engineering technologies offer the integration of components of the tumor microenvironment which are known to impair drug response of cancer cells. We established three-dimensional (3D) lung carcinoma models on a decellularized tissue matrix, providing a complex microenvironment for cell growth. For model generation, we used two cell lines with (HCC827) or without (A549) an activating mutation of the epidermal growth factor receptor (EGFR), exhibiting different sensitivities to the EGFR inhibitor gefitinib. EGFR activation in HCC827 was inhibited by gefitinib, resulting in a significant reduction of proliferation (Ki-67 proliferation index) and in the induction of apoptosis (TUNEL staining, M30-ELISA). No significant effect was observed in conventional cell culture. Results from the 3D model correlated with the results of an in silico model that integrates the EGFR signaling network according to clinical data. The application of TGFβ1 induced tumor cell invasion, accompanied by epithelial-mesenchymal transition (EMT) both in vitro and in silico. This was confirmed in the 3D model by acquisition of mesenchymal cell morphology and modified expression of fibronectin, E-cadherin, β-catenin and mucin-1. Quantitative read-outs for proliferation, apoptosis and invasion were established in the complex 3D tumor model. The combined in vitro and in silico model represents a powerful tool for systems analysis.

Indexed as

Models, BiologicalTumor MicroenvironmentAnimalsAntineoplastic AgentsApoptosisCell Culture TechniquesCell Line, TumorGefitinibHumansLung NeoplasmsNeoplasm InvasivenessNeoplasm ProteinsQuinazolinesSignal TransductionSwineAntineoplastic AgentsGefitinibNeoplasm ProteinsQuinazolines3D tumor modelBoolean modelEMTInvasionPersonalized medicineTargeted therapy

Identifiers

PMID24388494
PMCPMC5528544
OpenAlexW2035954579

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.